mlsanityData to 14 Oct 2026

ROS2SmolVLA: Enabling Small Vision-Language-Action Models for Integration into Industrial-Grade Lightweight Robots

arXiv 2608.23320 ↗First posted 24 Aug 2026cs.ROcited by 0

On the map: Vision-language-action models → Generalist VLA models and benchmarks

Abstract (arXiv)

Industrial demand changes the paradigms of production. Due to smaller batch sizes and more variations in products, companies face a growing challenge to adopt more adaptive production systems. In particular, robot-based automation is usually static and fails to respond to constantly changing processes. Vision-Language-Action (VLA) Models are a promising opportunity to mitigate this challenge by generating robot actions based on the observed system state. However, current research either focuses on large models that cannot be computed on premise, creating compliance and security challenges, or use lab-grade robot hardware that obscures exploitation in real industrial settings. In this work, we adapt Hugging Face's SmolVLA for Universal Robots lightweight robots. Further, we release the open-source repository ROS2SmolVLA that implements an interface for ROS 2 to SmolVLA, and makes it applicable for industrial-grade hardware. By this, we allow a lenient adoption into lab and industrial environments. We validate the functionality of SmolVLA for a Universal Robots UR10e using a pick-and-place task and give implementation guidelines. Our findings support that SmolVLA is a well-suited option for small-sized tasks that need to be computed on premise.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Generalist VLA models and benchmarks, one of 13 directions in Vision-language-action models. Builds on 18 of its 30 references that are in the map. First posted on arXiv 24 Aug 2026.

Builds on

18 of 30 references.

Closest ancestors · 4

Same direction, newest first

  1. 2026Adaptive Capacity Allocation for Vision Language Action Fine-tuning8 Mar
  2. 2025Vision-Language-Action Models for Robotics: A Review Towards Real-World Applications8 Oct
  3. 2025SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics2 Jun
  4. 2024OpenVLA: An Open-Source Vision-Language-Action Model13 Jun

Other references · 14

  1. 2023PaLM-E: An Embodied Multimodal Language Modelcited by 2,071
  2. 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,061
  3. 2024Octo: An Open-Source Generalist Robot Policycited by 1,484
  4. 2023Open X-Embodiment: Robotic Learning Datasets and RT-X Modelscited by 862
  5. 2025SmolVLM: Redefining small and efficient multimodal modelscited by 237
  6. 2025Real-Time Execution of Action Chunking Flow Policiescited by 216
  7. 2025PD-VLA: Accelerating Vision-Language-Action Model Integrated with Action Chunking via Parallel Decodingcited by 88
  8. 2026LeRobot: An Open-Source Library for End-to-End Robot Learningcited by 73
  9. 2024Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigationcited by 60
  10. 2024Low-Rank Adaptation for Foundation Models: A Comprehensive Reviewcited by 37
  11. 2024Large Language Models for Manufacturingcited by 24
  12. 2026PokeVLA: Empowering Pocket-Sized Vision-Language-Action Model with Comprehensive World Knowledge Guidancecited by 6
2 more
  1. 2026Benchmarking Vision-Language-Action Models on SO-101: Failure and Recovery Analysiscited by 4
  2. 2026Squint: Fast Visual Reinforcement Learning for Sim-to-Real Roboticscited by 2

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  1. 2025An Anatomy of Vision-Language-Action Models: From Modules to Milestones and Challenges
  2. 2025VLA-0: Building State-of-the-Art VLAs with Zero Modification
  3. 2026Efficient Vision-Language-Action Management and Serving for Robot Factories
  4. 2025Transferring Vision-Language-Action Models to Industry Applications: Architectures, Performance, and Challenges
  5. 2026StarVLA-α: Reducing Complexity in Vision-Language-Action Systems
  6. 2026SimVLA: A Simple VLA Baseline for Robotic Manipulation
  7. 2024What Matters in Building Vision-Language-Action Models for Generalist Robots
  8. 2026RhinoVLA Technical Report